BACKGROUND Genetic studies of neuropsychiatric disease strongly suggest an overlap in liability. There are growing efforts to characterize these diseases dimensionally rather than categorically, but the extent to which such dimensional models correspond to biology is unknown. METHODS We applied a newly developed natural language processing method to extract five symptom dimensions based on the National Institute of Mental Health Research Domain Criteria definitions from narrative hospital discharge notes in a large biobank. We conducted a genome-wide association study to examine whether common variants were associated with each of these dimensions as quantitative traits. RESULTS Among 4687 individuals, loci in three of five domains exceeded a genome-wide threshold for statistical significance. These included a locus spanning the neocortical development genes RFPL3 and RFPL3S for arousal (p = 2.29 × 10-8) and one spanning the FPR3 gene for cognition (p = 3.22 × 10-8). CONCLUSIONS Natural language processing identifies dimensional phenotypes that may facilitate the discovery of common genetic variation that is relevant to psychopathology.

中文翻译：

---

使用电子健康记录进行维度精神病理学的全基因组关联研究

背景神经精神疾病的遗传研究强烈表明责任重叠。越来越多的努力从维度而非分类来表征这些疾病，但此类维度模型在多大程度上与生物学相符尚不清楚。方法 我们应用新开发的自然语言处理方法，根据美国国家心理健康研究所领域标准定义，从大型生物库的叙述性出院记录中提取五个症状维度。我们进行了一项全基因组关联研究，以检查常见变异是否与作为数量性状的每个维度相关。结果 在 4687 个个体中，五个域中的三个域中的基因座超过了统计显着性的全基因组阈值。这些包括一个跨越新皮质发育基因 RFPL3 和 RFPL3S 的基因座（p = 2.29 × 10-8）和一个跨越 FPR3 基因的基因座（p = 3.22 × 10-8）。结论 自然语言处理可识别维度表型，这些表型可能有助于发现与精神病理学相关的常见遗传变异。